
================================================================================
                      RDC Logit Model - Parameter Estimates

   iteration:  10  
   algorithm: BFGS         step method: STEPBT 
   function:  0.49470      step length:  1.00000      backsteps:  0  
--------------------------------------------------------------------------------
   param.      param. value     relative grad.
       1            -0.0348            0.2531
       2             0.0213            0.0284
       3            -0.0196            0.0035
       4             0.0118            0.0756
       5            -0.0420            0.0088
       6             0.0127            0.0607
       7            -0.0188            0.0948
       8            -0.0098            0.1450
       9            -0.0048            0.0026
      10            -0.0099            0.0065
      11             0.0137            0.0104
      12             0.0026            0.0037

================================================================================
                      RDC Logit Model - Parameter Estimates

   iteration:  20  
   algorithm: BFGS         step method: STEPBT 
   function:  0.48944      step length:  1.00000      backsteps:  0  
--------------------------------------------------------------------------------
   param.      param. value     relative grad.
       1            -0.0471            0.0097
       2             0.0200            0.0147
       3            -0.0203            0.0106
       4             0.0147            0.0060
       5            -0.0413            0.0014
       6             0.0106            0.0033
       7            -0.0082            0.0040
       8            -0.0110            0.0275
       9            -0.0364            0.0016
      10            -0.1393            0.0021
      11             0.4331            0.0050
      12             0.2823            0.0059

================================================================================
                      RDC Logit Model - Parameter Estimates

   iteration:  30  
   algorithm: BFGS         step method: STEPBT 
   function:  0.48731      step length:  1.00000      backsteps:  0  
--------------------------------------------------------------------------------
   param.      param. value     relative grad.
       1            -0.0509            0.0001
       2             0.0189            0.0014
       3            -0.0178            0.0060
       4             0.0137            0.0015
       5            -0.0348            0.0000
       6             0.0092            0.0006
       7            -0.0060            0.0013
       8            -0.0120            0.0034
       9            -0.1624            0.0040
      10            -0.3638            0.0057
      11             0.3425            0.0007
      12             0.8097            0.0034

================================================================================
                      RDC Logit Model - Parameter Estimates

   iteration:  40  
   algorithm: BFGS         step method: STEPBT 
   function:  0.48604      step length:  1.00000      backsteps:  0  
--------------------------------------------------------------------------------
   param.      param. value     relative grad.
       1            -0.0560            0.0000
       2             0.0163            0.0000
       3            -0.0152            0.0005
       4             0.0115            0.0000
       5            -0.0251            0.0000
       6             0.0079            0.0001
       7            -0.0023            0.0000
       8            -0.0161            0.0000
       9            -0.0806            0.0007
      10            -0.2683            0.0006
      11             0.2644            0.0001
      12             1.2736            0.0001

===============================================================================
                     RDC Logit Model - Parameter Estimates                     
===============================================================================
 MAXLIK Version 5.0.9                                     11/23/2021   2:52 pm
===============================================================================

return code =    0
normal convergence

Mean log-likelihood       -0.486027
Number of cases     7584

Covariance matrix of the parameters computed by the following method:
QML covariance matrix

Parameters    Estimates     Std. err.  Est./s.e.  Prob.    Gradient
------------------------------------------------------------------
P01             -0.0562        0.0034  -16.435   0.0000      0.0000
P02              0.0162        0.0036    4.506   0.0000      0.0000
P03             -0.0152        0.0039   -3.940   0.0001      0.0000
P04              0.0114        0.0030    3.832   0.0001      0.0000
P05             -0.0248        0.0087   -2.840   0.0045      0.0000
P06              0.0079        0.0022    3.537   0.0004      0.0000
P07             -0.0022        0.0047   -0.463   0.6437      0.0000
P08             -0.0162        0.0029   -5.683   0.0000      0.0000
P09             -0.1010        0.1026   -0.984   0.3250      0.0000
P10             -0.2496        0.1215   -2.054   0.0400      0.0000
P11              0.2654        0.1025    2.590   0.0096      0.0000
P12              1.2880        0.2250    5.724   0.0000      0.0000

Correlation matrix of the parameters
   1.000   0.114  -0.107   0.176  -0.077   0.198  -0.014   0.125   0.058   0.009   0.000  -0.491
   0.114   1.000   0.024   0.102  -0.174  -0.071   0.273   0.016  -0.048  -0.058   0.006  -0.177
  -0.107   0.024   1.000   0.193   0.155  -0.040   0.053  -0.029   0.099   0.088  -0.023   0.209
   0.176   0.102   0.193   1.000   0.039   0.135   0.175   0.002   0.059   0.059  -0.032  -0.198
  -0.077  -0.174   0.155   0.039   1.000   0.176  -0.171  -0.005  -0.001   0.010  -0.035   0.254
   0.198  -0.071  -0.040   0.135   0.176   1.000   0.014  -0.001   0.008   0.069  -0.061  -0.181
  -0.014   0.273   0.053   0.175  -0.171   0.014   1.000  -0.068   0.054   0.019   0.049   0.137
   0.125   0.016  -0.029   0.002  -0.005  -0.001  -0.068   1.000  -0.027  -0.131  -0.047  -0.608
   0.058  -0.048   0.099   0.059  -0.001   0.008   0.054  -0.027   1.000  -0.145  -0.065  -0.107
   0.009  -0.058   0.088   0.059   0.010   0.069   0.019  -0.131  -0.145   1.000  -0.066  -0.276
   0.000   0.006  -0.023  -0.032  -0.035  -0.061   0.049  -0.047  -0.065  -0.066   1.000  -0.246
  -0.491  -0.177   0.209  -0.198   0.254  -0.181   0.137  -0.608  -0.107  -0.276  -0.246   1.000

Number of iterations    45
Minutes to convergence     0.00323
      -3686.0293 
